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Record W4406950186 · doi:10.1177/20543581241307064

The Evaluation of Change in Psychosocial Risk With Caregivers of Children With Chronic Kidney Disease: A Short-term Longitudinal Mixed-Methods Study

2025· article· en· W4406950186 on OpenAlexaffabout
Caroline C. Piotrowski, Kira Kudar, Julie Strong, Ashley Giesbrecht, Anne E. Kazak, Katerina V. Pappas, Gina Rempel, Aviva Goldberg

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2025
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsHealth Sciences CentreChildren's Hospital of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsPsychosocialMedicineThematic analysisPandemicKidney diseaseGerontologyLongitudinal studyQualitative researchFamily medicineDiseasePsychiatryCoronavirus disease 2019 (COVID-19)Infectious disease (medical specialty)Internal medicine

Abstract

fetched live from OpenAlex

Background: The COVID-19 pandemic and its accompanying safeguards intensified many of the ongoing daily challenges faced by caregivers of young people with chronic kidney disease (CKD) both pre-transplant and post-transplant, and also created a variety of new and pressing concerns. Little is known about how these families managed this unexpected adversity in their lives. Objective: To evaluate change in psychosocial risk for families of young people with CKD during the COVID-19 pandemic health emergency from the perspective of caregivers. Design: A short-term longitudinal mixed-methods study with a convergent parallel design. Setting: Manitoba, Canada. Participants: Thirty-six caregivers of young people with CKD participated in a quantitative assessment prior to the pandemic; approximately half were transplant recipients. Thirteen were re-assessed during the pandemic (62% were caregivers of transplant recipients) using both qualitative and quantitative assessments. Methods: First, caregivers completed the Psychosocial Assessment Tool (PAT) prior to the pandemic. Second, caregivers were re-assessed using the PAT during the pandemic. They were also interviewed about their experiences. Changes in PAT scores over time were evaluated, including an investigation of whether psychosocial risk was related to transplant status. Interviews were coded using thematic analysis. In the interpretation stage, the qualitative findings were combined with the quantitative results to help explain the latter and reach a more fulsome understanding of caregivers' experience. Results: Quantitatively, overall family psychosocial risk scores increased significantly during the pandemic health emergency, as did the domain of Caregiver Problems. Families of transplant recipients were found to be at significantly lower psychosocial risk pre-pandemic than families of transplant candidates. Coding identified Negative Pandemic Experiences, Positive Pandemic Experiences, and Coping Mechanisms. Mixed-methods analyses revealed several areas of convergence and divergence between the quantitative and qualitative findings. Limitations: Limitations included a small sample size that limited generalizability, single site data collection, and single caregiver report. Conclusions: Although overall family psychosocial risk increased during the pandemic, caregivers described several resilience processes and characteristics. A mixed-method approach provided a unique perspective that highlighted the value of integrating quantitative and qualitative findings. Results were discussed within the pediatric psychosocial preventive health model framework.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0050.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.404
Teacher spread0.359 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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